{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/N/project/suicide_study/pnas_replication/results/log/mi_5.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}20 Aug 2020, 05:05:12
{txt}
{com}. 
. if ("`model'" == "logit"){c -(}
.         use "${c -(}home_dir{c )-}/data/processed/suicide_reg_v1_raw.dta", clear
. {c )-}
{txt}
{com}. 
. if ("`model'" == "mi") {c -(}
.         use "${c -(}home_dir{c )-}/data/processed/suicide_reg_v1_imputed_M10.dta", clear  
. {c )-}
{txt}
{com}. 
. * for now, we use the following simple survey weights 
. if ("`model'" == "mi") {c -(}
.         mi svyset `geo_type' [pw=ObsWgt0] 
{res}
      {txt}pweight:{col 16}{res}ObsWgt0
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}{res}county
        {txt}FPC 1:{col 16}<zero>
{p2colreset}{...}
{res}{com}. {c )-}
{txt}
{com}. else {c -(}
.         svyset `geo_type' [pw=ObsWgt0]  
. {c )-}
{txt}
{com}. 
. * margins for each category
. program margin_interact 
{txt}  1{com}.         args X Y k model
{txt}  2{com}.         sum `X', d 
{txt}  3{com}.         local gap = (`r(max)' - `r(min)') / `k' 
{txt}  4{com}.         if ("`model'" == "logit") {c -(}
{txt}  5{com}.                 margin `Y', at(`X' = (`r(min)' (`gap') `r(max)')) predict(pr)
{txt}  6{com}.         {c )-} 
{txt}  7{com}.         else if ("`model'" == "mi") {c -(}
{txt}  8{com}.                 mimrgns `Y', at(`X' = (`r(min)' (`gap') `r(max)')) predict(pr)
{txt}  9{com}.         {c )-}       
{txt} 10{com}. end 
{txt}
{com}. 
. program mchange_mi
{txt}  1{com}.         args X k model
{txt}  2{com}.         if ("`model'" == "logit") {c -(}
{txt}  3{com}. 
.                 if ("`k'" == "continuous") {c -(}
{txt}  4{com}.                         sum `X' if e(sample), d 
{txt}  5{com}.                         margin, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt}  6{com}.                         mlincom  2 - 1, decimal(7) stat(all)    
{txt}  7{com}.                 {c )-} 
{txt}  8{com}.                 else if ("`k'" == "binary") {c -(}
{txt}  9{com}.                         sum `X' if e(sample), d 
{txt} 10{com}.                         margin, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 11{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 12{com}.                 {c )-} 
{txt} 13{com}.                 else if ("`k'" == "categorical") {c -(}
{txt} 14{com}.                         margin `X' if e(sample)==1 , at() pwcompare predict(pr) 
{txt} 15{com}.                 {c )-}
{txt} 16{com}.         {c )-}
{txt} 17{com}. 
.         else if ("`model'" == "mi") {c -(}
{txt} 18{com}. 
.                 if ("`k'" == "continuous") {c -(}
{txt} 19{com}.                         sum `X' , d 
{txt} 20{com}.                         mimrgns, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 21{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 22{com}.                 {c )-} 
{txt} 23{com}.                 else if ("`k'" == "binary") {c -(}
{txt} 24{com}.                         sum `X' , d 
{txt} 25{com}.                         mimrgns, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 26{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 27{com}.                 {c )-} 
{txt} 28{com}.                 else if ("`k'" == "categorical") {c -(}
{txt} 29{com}.                         mimrgns `X' , at()   pwcompare predict(pr)      
{txt} 30{com}.                 {c )-}
{txt} 31{com}.         {c )-}
{txt} 32{com}. end
{txt}
{com}. 
. * create some dummy codings
. tab Race5, gen(race5_nh)

      {txt}Race5 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}107,831,845       79.53       79.53
{txt}          2 {c |}{res} 14,631,144       10.79       90.32
{txt}          3 {c |}{res}  2,867,304        2.11       92.44
{txt}          4 {c |}{res}  2,753,311        2.03       94.47
{txt}          5 {c |}{res}  7,499,129        5.53      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}135,582,733      100.00
{txt}
{com}.         rename race5_nh1 White_nh 
{res}{txt}
{com}.         rename race5_nh2 Black_nh 
{res}{txt}
{com}.         rename race5_nh3 AIAN_nh 
{res}{txt}
{com}.         rename race5_nh4 AsPI_nh 
{res}{txt}
{com}.         rename race5_nh5 Hispanic
{res}{txt}
{com}. 
. tab MarStat5, gen(ms)

   {txt}MarStat5 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res} 75,689,936       55.83       55.83
{txt}          2 {c |}{res} 10,166,664        7.50       63.32
{txt}          3 {c |}{res} 13,925,509       10.27       73.60
{txt}          4 {c |}{res}  2,609,308        1.92       75.52
{txt}          5 {c |}{res} 33,190,855       24.48      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}135,582,272      100.00
{txt}
{com}.         rename ms1 Marrd5
{res}{txt}
{com}.         rename ms2 Widow5
{res}{txt}
{com}.         rename ms3 Divor5
{res}{txt}
{com}.         rename ms4 Separ5
{res}{txt}
{com}.         rename ms5 NvMar5
{res}{txt}
{com}. 
. tab AgeGrp4, gen(ag) 

    {txt}AgeGrp4 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res} 21,231,562       15.66       15.66
{txt}          2 {c |}{res} 39,043,312       28.80       44.46
{txt}          3 {c |}{res} 47,351,260       34.92       79.38
{txt}          4 {c |}{res} 27,956,599       20.62      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}135,582,733      100.00
{txt}
{com}.         rename ag1 Age_15_24
{res}{txt}
{com}.         rename ag2 Age_25_44
{res}{txt}
{com}.         rename ag3 Age_45_64
{res}{txt}
{com}.         rename ag4 Age_65_Up
{res}{txt}
{com}. 
. destring St, replace 
{txt}St: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. 
. * set-up equations
. local religion Rat_GC_ProE Rat_GC_ProM Rat_GC_ProB Rat_GC_Cath Rat_GC_Jew Rat_GC_Oth
{txt}
{com}. local contextual_control Rat_Poverty Rat_Mig_Cum Pop_Den
{txt}
{com}. 
. local religion Rat_GC_ProE Rat_GC_ProM Rat_GC_ProB Rat_GC_Jew Rat_GC_Oth
{txt}
{com}. local contextual_control Rat_Poverty Rat_Mig_Cum Pop_Den
{txt}
{com}. 
. local demographics_raw i.Female c.RAT_Female i.AgeGrp4 c.RAT_AgeGrp4_2 c.RAT_AgeGrp4_3 c.RAT_AgeGrp4_4 i.Race5 c.RAT_Race5_2 c.RAT_Race5_3 c.RAT_Race5_4 c.RAT_Race5_5 i.BornUSA c.RAT_BornUSA i.MarStat5 c.RAT_MarStat5_2 c.RAT_MarStat5_3 c.RAT_MarStat5_4 c.RAT_MarStat5_5
{txt}
{com}. local demographics_same i.Female c.std_same_prop_Sex i.AgeGrp4 c.std_same_prop_AgeGrp4 i.Race5 c.std_same_prop_Race5 i.BornUSA c.std_same_prop_BornUSA i.MarStat5 c.std_same_prop_MarStat5 
{txt}
{com}. local demographics_inter i.Female##c.std_same_prop_Sex i.AgeGrp4##c.std_same_prop_AgeGrp4 i.Race5##c.std_same_prop_Race5 i.BornUSA##c.std_same_prop_BornUSA i.MarStat5##c.std_same_prop_MarStat5
{txt}
{com}. 
. 
. if (`model_version' == 1){c -(}
.         local model_eq i.Year `demographics_raw' `contextual_control' `religion' 
.         local margin_demographics Female RAT_Female AgeGrp4 RAT_AgeGrp4_2 RAT_AgeGrp4_3 RAT_AgeGrp4_4 Race5 RAT_Race5_2 RAT_Race5_3 RAT_Race5_4 RAT_Race5_5 BornUSA RAT_BornUSA MarStat5 RAT_MarStat5_2 RAT_MarStat5_3 RAT_MarStat5_4 RAT_MarStat5_5 
. {c )-}
{txt}
{com}. if (`model_version' == 2){c -(}
.         local model_eq i.Year `demographics_raw' `contextual_control' `religion' i.UnEmpl c.RAT_UnEmpl i.PhysProb c.RAT_PhysProb
.         local margin_demographics Female RAT_Female AgeGrp4 RAT_AgeGrp4_2 RAT_AgeGrp4_3 RAT_AgeGrp4_4 Race5 RAT_Race5_2 RAT_Race5_3 RAT_Race5_4 RAT_Race5_5 BornUSA RAT_BornUSA MarStat5 RAT_MarStat5_2 RAT_MarStat5_3 RAT_MarStat5_4 RAT_MarStat5_5 UnEmpl RAT_UnEmpl PhysProb RAT_PhysProb
. {c )-}
{txt}
{com}. if (`model_version' == 3){c -(}
.         local model_eq i.Year `demographics_same' `contextual_control' `religion' 
.         local margin_demographics Female std_same_prop_Sex AgeGrp4 std_same_prop_AgeGrp4 Race5 std_same_prop_Race5 BornUSA std_same_prop_BornUSA MarStat5 std_same_prop_MarStat5 
. {c )-}
{txt}
{com}. if (`model_version' == 4){c -(}
.         local model_eq i.Year `demographics_same' `contextual_control' `religion' i.UnEmpl c.std_same_prop_UnEmpl i.PhysProb c.std_same_prop_PhysProb
.         local margin_demographics Female std_same_prop_Sex AgeGrp4 std_same_prop_AgeGrp4 Race5 std_same_prop_Race5 BornUSA std_same_prop_BornUSA MarStat5 std_same_prop_MarStat5 UnEmpl std_same_prop_UnEmpl PhysProb std_same_prop_PhysProb
. {c )-}
{txt}
{com}. if (`model_version' == 5){c -(}
.         local model_eq i.Year `demographics_inter' `contextual_control' `religion' 
. {c )-}
{txt}
{com}. if (`model_version' == 6){c -(}
.         local model_eq i.Year `demographics_inter' `contextual_control' `religion' i.UnEmpl##c.std_same_prop_UnEmpl i.PhysProb##c.std_same_prop_PhysProb
. {c )-}       
{txt}
{com}. * test how long it would take.
. * mi estimate: svy: mean Suic 
. * local demographics i.Female c.RAT_Female i.AgeGrp4 c.RAT_AgeGrp4_2 c.RAT_AgeGrp4_3 c.RAT_AgeGrp4_4 i.Race5 c.RAT_Race5_2 c.RAT_Race5_3 c.RAT_Race5_4 c.RAT_Race5_5 i.BornUSA c.RAT_BornUSA i.MarStat5 c.RAT_MarStat5_2 c.RAT_MarStat5_3 c.RAT_MarStat5_4 c.RAT_MarStat5_5
. * mi estimate: svy: logit Suic i.St `demographics' UnEmpl RAT_UnEmpl PhysProb RAT_PhysProb
. 
. * main effects : margins
. if ("`model'" == "mi"){c -(}
. 
.         mi estimate: svy: logit Suic i.St `model_eq', or 
{res}
{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Survey: Logistic regression{col 47}Number of obs{col 65}= {res}  11,814,307

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918
{txt}{col 47}Average RVI{col 65}= {res}      0.0007
{txt}{col 47}Largest FMI{col 65}= {res}      0.0036
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      910.56
{txt}{col 47}        avg{col 65}= {res}      914.52
{txt}{col 47}        max{col 65}= {res}      915.01
{txt}Model F test:{ralign 16: {res:Equal FMI}}{col 47}F({res}  60{txt},{res}  915.0{txt}){col 65}= {res}      626.67
{txt}Within VCE type: {ralign 12:{res:Linearized}}{col 47}Prob > F{col 65}= {res}      0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}        Suic{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}St {c |}
{space 10}8  {c |}{col 14}{res}{space 2} -.074926{col 26}{space 2} .0867705{col 37}{space 1}   -0.86{col 46}{space 3}0.388{col 54}{space 4}-.2452182{col 67}{space 3} .0953663
{txt}{space 9}13  {c |}{col 14}{res}{space 2}-.4307346{col 26}{space 2}  .088791{col 37}{space 1}   -4.85{col 46}{space 3}0.000{col 54}{space 4}-.6049923{col 67}{space 3}-.2564769
{txt}{space 9}21  {c |}{col 14}{res}{space 2}-.5433186{col 26}{space 2} .0873249{col 37}{space 1}   -6.22{col 46}{space 3}0.000{col 54}{space 4} -.714699{col 67}{space 3}-.3719382
{txt}{space 9}24  {c |}{col 14}{res}{space 2}-.6611568{col 26}{space 2} .0878774{col 37}{space 1}   -7.52{col 46}{space 3}0.000{col 54}{space 4}-.8336216{col 67}{space 3}-.4886921
{txt}{space 9}25  {c |}{col 14}{res}{space 2}-.9145031{col 26}{space 2} .0872385{col 37}{space 1}  -10.48{col 46}{space 3}0.000{col 54}{space 4}-1.085714{col 67}{space 3}-.7432923
{txt}{space 9}34  {c |}{col 14}{res}{space 2}-.8080827{col 26}{space 2} .0917368{col 37}{space 1}   -8.81{col 46}{space 3}0.000{col 54}{space 4}-.9881217{col 67}{space 3}-.6280437
{txt}{space 9}35  {c |}{col 14}{res}{space 2}-.0689877{col 26}{space 2} .1024009{col 37}{space 1}   -0.67{col 46}{space 3}0.501{col 54}{space 4}-.2699556{col 67}{space 3} .1319802
{txt}{space 9}37  {c |}{col 14}{res}{space 2}  -.40215{col 26}{space 2} .0927417{col 37}{space 1}   -4.34{col 46}{space 3}0.000{col 54}{space 4} -.584161{col 67}{space 3}-.2201389
{txt}{space 9}40  {c |}{col 14}{res}{space 2}-.5665228{col 26}{space 2} .0958834{col 37}{space 1}   -5.91{col 46}{space 3}0.000{col 54}{space 4}-.7546998{col 67}{space 3}-.3783458
{txt}{space 9}41  {c |}{col 14}{res}{space 2}-.2310185{col 26}{space 2} .0852477{col 37}{space 1}   -2.71{col 46}{space 3}0.007{col 54}{space 4}-.3983222{col 67}{space 3}-.0637149
{txt}{space 9}44  {c |}{col 14}{res}{space 2}-.7721976{col 26}{space 2} .0872468{col 37}{space 1}   -8.85{col 46}{space 3}0.000{col 54}{space 4}-.9434246{col 67}{space 3}-.6009706
{txt}{space 9}45  {c |}{col 14}{res}{space 2}-.4488899{col 26}{space 2} .0893646{col 37}{space 1}   -5.02{col 46}{space 3}0.000{col 54}{space 4}-.6242732{col 67}{space 3}-.2735066
{txt}{space 9}49  {c |}{col 14}{res}{space 2} .6260656{col 26}{space 2} .1725918{col 37}{space 1}    3.63{col 46}{space 3}0.000{col 54}{space 4} .2873438{col 67}{space 3} .9647874
{txt}{space 9}51  {c |}{col 14}{res}{space 2}-.3388622{col 26}{space 2} .0857812{col 37}{space 1}   -3.95{col 46}{space 3}0.000{col 54}{space 4} -.507213{col 67}{space 3}-.1705115
{txt}{space 9}55  {c |}{col 14}{res}{space 2}-.6090685{col 26}{space 2} .0877629{col 37}{space 1}   -6.94{col 46}{space 3}0.000{col 54}{space 4}-.7813085{col 67}{space 3}-.4368285
{txt}{space 12} {c |}
{space 8}Year {c |}
{space 7}2006  {c |}{col 14}{res}{space 2}-.0617763{col 26}{space 2} .0181357{col 37}{space 1}   -3.41{col 46}{space 3}0.001{col 54}{space 4}-.0973686{col 67}{space 3} -.026184
{txt}{space 7}2007  {c |}{col 14}{res}{space 2} .0129257{col 26}{space 2}  .018419{col 37}{space 1}    0.70{col 46}{space 3}0.483{col 54}{space 4}-.0232228{col 67}{space 3} .0490741
{txt}{space 7}2008  {c |}{col 14}{res}{space 2}  .014674{col 26}{space 2} .0200625{col 37}{space 1}    0.73{col 46}{space 3}0.465{col 54}{space 4}-.0246999{col 67}{space 3} .0540479
{txt}{space 7}2009  {c |}{col 14}{res}{space 2} .0692964{col 26}{space 2} .0188169{col 37}{space 1}    3.68{col 46}{space 3}0.000{col 54}{space 4} .0323671{col 67}{space 3} .1062258
{txt}{space 7}2010  {c |}{col 14}{res}{space 2} .0565532{col 26}{space 2} .0204991{col 37}{space 1}    2.76{col 46}{space 3}0.006{col 54}{space 4} .0163225{col 67}{space 3} .0967838
{txt}{space 7}2011  {c |}{col 14}{res}{space 2} .0954203{col 26}{space 2} .0221895{col 37}{space 1}    4.30{col 46}{space 3}0.000{col 54}{space 4} .0518722{col 67}{space 3} .1389685
{txt}{space 12} {c |}
{space 4}1.Female {c |}{col 14}{res}{space 2}-1.389345{col 26}{space 2} .0154624{col 37}{space 1}  -89.85{col 46}{space 3}0.000{col 54}{space 4}-1.419691{col 67}{space 3}-1.358999
{txt}std_same_p~x {c |}{col 14}{res}{space 2}-.0139282{col 26}{space 2} .0110646{col 37}{space 1}   -1.26{col 46}{space 3}0.208{col 54}{space 4}-.0356432{col 67}{space 3} .0077867
{txt}{space 12} {c |}
{space 6}Female#{c |}
{space 10}c. {c |}
std_same_p~x {c |}
{space 10}1  {c |}{col 14}{res}{space 2}-.0087894{col 26}{space 2} .0219091{col 37}{space 1}   -0.40{col 46}{space 3}0.688{col 54}{space 4}-.0517872{col 67}{space 3} .0342085
{txt}{space 12} {c |}
{space 5}AgeGrp4 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .7976225{col 26}{space 2} .0210616{col 37}{space 1}   37.87{col 46}{space 3}0.000{col 54}{space 4} .7562878{col 67}{space 3} .8389573
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .8874785{col 26}{space 2} .0252884{col 37}{space 1}   35.09{col 46}{space 3}0.000{col 54}{space 4} .8378483{col 67}{space 3} .9371087
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .6964385{col 26}{space 2} .0272906{col 37}{space 1}   25.52{col 46}{space 3}0.000{col 54}{space 4} .6428789{col 67}{space 3} .7499982
{txt}{space 12} {c |}
std_same_p~4 {c |}{col 14}{res}{space 2}-.0404995{col 26}{space 2}  .017791{col 37}{space 1}   -2.28{col 46}{space 3}0.023{col 54}{space 4}-.0754153{col 67}{space 3}-.0055836
{txt}{space 12} {c |}
{space 5}AgeGrp4#{c |}
{space 10}c. {c |}
std_same_p~4 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.0411575{col 26}{space 2} .0197088{col 37}{space 1}   -2.09{col 46}{space 3}0.037{col 54}{space 4}-.0798373{col 67}{space 3}-.0024777
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .0185155{col 26}{space 2} .0213655{col 37}{space 1}    0.87{col 46}{space 3}0.386{col 54}{space 4}-.0234156{col 67}{space 3} .0604467
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0740566{col 26}{space 2}  .024783{col 37}{space 1}    2.99{col 46}{space 3}0.003{col 54}{space 4} .0254185{col 67}{space 3} .1226947
{txt}{space 12} {c |}
{space 7}Race5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.9281708{col 26}{space 2} .0329507{col 37}{space 1}  -28.17{col 46}{space 3}0.000{col 54}{space 4}-.9928385{col 67}{space 3}-.8635031
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.0927045{col 26}{space 2}  .077812{col 37}{space 1}   -1.19{col 46}{space 3}0.234{col 54}{space 4}-.2454152{col 67}{space 3} .0600062
{txt}{space 10}4  {c |}{col 14}{res}{space 2}-.5573767{col 26}{space 2} .0574981{col 37}{space 1}   -9.69{col 46}{space 3}0.000{col 54}{space 4}-.6702202{col 67}{space 3}-.4445333
{txt}{space 10}5  {c |}{col 14}{res}{space 2}-.7848995{col 26}{space 2} .0449982{col 37}{space 1}  -17.44{col 46}{space 3}0.000{col 54}{space 4}-.8732111{col 67}{space 3}-.6965879
{txt}{space 12} {c |}
std_same_~e5 {c |}{col 14}{res}{space 2}-.0361749{col 26}{space 2} .0147892{col 37}{space 1}   -2.45{col 46}{space 3}0.015{col 54}{space 4}-.0651997{col 67}{space 3}-.0071502
{txt}{space 12} {c |}
{space 7}Race5#{c |}
{space 10}c. {c |}
std_same_~e5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}-.0213858{col 26}{space 2} .0330534{col 37}{space 1}   -0.65{col 46}{space 3}0.518{col 54}{space 4}-.0862552{col 67}{space 3} .0434835
{txt}{space 10}3  {c |}{col 14}{res}{space 2}  .114744{col 26}{space 2} .0542761{col 37}{space 1}    2.11{col 46}{space 3}0.035{col 54}{space 4} .0082239{col 67}{space 3} .2212641
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .0981811{col 26}{space 2} .0228955{col 37}{space 1}    4.29{col 46}{space 3}0.000{col 54}{space 4} .0532472{col 67}{space 3} .1431149
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .1150823{col 26}{space 2} .0261017{col 37}{space 1}    4.41{col 46}{space 3}0.000{col 54}{space 4} .0638561{col 67}{space 3} .1663084
{txt}{space 12} {c |}
{space 3}1.BornUSA {c |}{col 14}{res}{space 2} .4583133{col 26}{space 2} .0411103{col 37}{space 1}   11.15{col 46}{space 3}0.000{col 54}{space 4} .3776319{col 67}{space 3} .5389946
{txt}std_same_p~A {c |}{col 14}{res}{space 2}-.0430026{col 26}{space 2} .0176028{col 37}{space 1}   -2.44{col 46}{space 3}0.015{col 54}{space 4}-.0775492{col 67}{space 3} -.008456
{txt}{space 12} {c |}
{space 5}BornUSA#{c |}
{space 10}c. {c |}
std_same_p~A {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .0905416{col 26}{space 2} .0216105{col 37}{space 1}    4.19{col 46}{space 3}0.000{col 54}{space 4} .0481298{col 67}{space 3} .1329535
{txt}{space 12} {c |}
{space 4}MarStat5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .8025562{col 26}{space 2} .0234432{col 37}{space 1}   34.23{col 46}{space 3}0.000{col 54}{space 4} .7565473{col 67}{space 3} .8485652
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 1.132562{col 26}{space 2} .0145141{col 37}{space 1}   78.03{col 46}{space 3}0.000{col 54}{space 4} 1.104077{col 67}{space 3} 1.161047
{txt}{space 10}4  {c |}{col 14}{res}{space 2}-.0498861{col 26}{space 2} .0905325{col 37}{space 1}   -0.55{col 46}{space 3}0.582{col 54}{space 4}-.2275623{col 67}{space 3}   .12779
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .8013863{col 26}{space 2} .0177632{col 37}{space 1}   45.12{col 46}{space 3}0.000{col 54}{space 4} .7665248{col 67}{space 3} .8362478
{txt}{space 12} {c |}
std_same_~t5 {c |}{col 14}{res}{space 2}-.0561149{col 26}{space 2}  .011433{col 37}{space 1}   -4.91{col 46}{space 3}0.000{col 54}{space 4}-.0785529{col 67}{space 3}-.0336768
{txt}{space 12} {c |}
{space 4}MarStat5#{c |}
{space 10}c. {c |}
std_same_~t5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} -.051418{col 26}{space 2} .0259916{col 37}{space 1}   -1.98{col 46}{space 3}0.048{col 54}{space 4}-.1024282{col 67}{space 3}-.0004078
{txt}{space 10}3  {c |}{col 14}{res}{space 2}-.0033979{col 26}{space 2} .0162725{col 37}{space 1}   -0.21{col 46}{space 3}0.835{col 54}{space 4}-.0353337{col 67}{space 3} .0285379
{txt}{space 10}4  {c |}{col 14}{res}{space 2}-.1023588{col 26}{space 2} .0700905{col 37}{space 1}   -1.46{col 46}{space 3}0.145{col 54}{space 4} -.239916{col 67}{space 3} .0351984
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .0764298{col 26}{space 2} .0168913{col 37}{space 1}    4.52{col 46}{space 3}0.000{col 54}{space 4} .0432795{col 67}{space 3} .1095801
{txt}{space 12} {c |}
{space 1}Rat_Poverty {c |}{col 14}{res}{space 2}-.0012888{col 26}{space 2}  .001902{col 37}{space 1}   -0.68{col 46}{space 3}0.498{col 54}{space 4}-.0050216{col 67}{space 3} .0024441
{txt}{space 1}Rat_Mig_Cum {c |}{col 14}{res}{space 2}-1.721755{col 26}{space 2} .5217112{col 37}{space 1}   -3.30{col 46}{space 3}0.001{col 54}{space 4}-2.745645{col 67}{space 3}-.6978659
{txt}{space 5}Pop_Den {c |}{col 14}{res}{space 2} 9.59e-07{col 26}{space 2} 5.82e-06{col 37}{space 1}    0.16{col 46}{space 3}0.869{col 54}{space 4}-.0000105{col 67}{space 3} .0000124
{txt}{space 1}Rat_GC_ProE {c |}{col 14}{res}{space 2} .0000163{col 26}{space 2} 8.90e-06{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4}-1.14e-06{col 67}{space 3} .0000338
{txt}{space 1}Rat_GC_ProM {c |}{col 14}{res}{space 2}-3.08e-06{col 26}{space 2} .0000114{col 37}{space 1}   -0.27{col 46}{space 3}0.788{col 54}{space 4}-.0000255{col 67}{space 3} .0000193
{txt}{space 1}Rat_GC_ProB {c |}{col 14}{res}{space 2}-.0000978{col 26}{space 2} .0000428{col 37}{space 1}   -2.28{col 46}{space 3}0.023{col 54}{space 4}-.0001818{col 67}{space 3}-.0000137
{txt}{space 2}Rat_GC_Jew {c |}{col 14}{res}{space 2} .0000654{col 26}{space 2} .0000726{col 37}{space 1}    0.90{col 46}{space 3}0.368{col 54}{space 4}-.0000771{col 67}{space 3} .0002078
{txt}{space 2}Rat_GC_Oth {c |}{col 14}{res}{space 2}-.0001052{col 26}{space 2} .0000245{col 37}{space 1}   -4.30{col 46}{space 3}0.000{col 54}{space 4}-.0001533{col 67}{space 3}-.0000571
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-9.103725{col 26}{space 2} .1027731{col 37}{space 1}  -88.58{col 46}{space 3}0.000{col 54}{space 4}-9.305423{col 67}{space 3}-8.902026
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates store m1 
. 
.         if (`model_version' <= 4){c -(}
.                 estimates restore m1
.                 mchange_mi Female "binary" "mi"
.                 estimates restore m1
.                 mchange_mi AgeGrp4 "categorical" "mi"
.                 estimates restore m1
.                 mchange_mi Race5 "categorical" "mi"
.                 estimates restore m1
.                 mchange_mi BornUSA "binary" "mi"
.                 estimates restore m1
.                 mchange_mi MarStat5 "categorical" "mi"
.                 
.                 if (`model_version' == 1 | `model_version' == 2) {c -(}
.                         estimates restore m1
.                         mchange_mi RAT_Female "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_5 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_BornUSA "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_5 "continuous" "mi"
.                 {c )-}
.                 if (`model_version' == 3 | `model_version' == 4) {c -(}
.                         estimates restore m1
.                         mchange_mi std_same_prop_Sex "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_AgeGrp4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_Race5 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_BornUSA "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_MarStat5 "continuous" "mi"
.                 {c )-}
.         
.                 if (`model_version' == 2 | `model_version' == 4){c -(}
.                         estimates restore m1
.                         mchange_mi UnEmpl "categorical" "mi"
.                         estimates restore m1
.                         mchange_mi PhysProb "categorical" "mi"
.                 {c )-}
.         
.                 if (`model_version' == 2){c -(}
.                         estimates restore m1
.                         mchange_mi RAT_UnEmpl "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_PhysProb "continuous" "mi"
.                 {c )-}
.                 if (`model_version' == 4){c -(}
.                         estimates restore m1
.                         mchange_mi std_same_prop_UnEmpl "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_PhysProb "continuous" "mi"
.                 {c )-}               
.         {c )-}
. {c )-}
{txt}
{com}. 
. if ("`model'" == "logit"){c -(}
.         svy: logit Suic i.St `model_eq', or 
.         estimates store m1 
. 
.         if (`model_version' <= 4){c -(}
.                 mchange `margin_demographics', amount(all) delta(100) statistics(all) decimals(7)
.         {c )-}
. 
. {c )-}
{txt}
{com}. 
. if (`model_version' == 5 | `model_version' == 6) {c -(}
.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_Sex Female 5 `model'

                      {txt}std_same_prop_Sex
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.509072      -4.036727
{txt} 5%    {res}-1.338853      -4.036727
{txt}10%    {res}-.9852811      -4.036727       {txt}Obs         {res}135,582,733
{txt}25%    {res}-.5357422      -4.036727       {txt}Sum of Wgt. {res}  135582733

{txt}50%    {res} .0312444                      {txt}Mean          {res}  .027466
                        {txt}Largest       Std. Dev.     {res} .9119966
{txt}75%    {res} .5763232       4.036727
{txt}90%    {res} 1.032018       4.036727       {txt}Variance      {res} .8317377
{txt}95%    {res} 1.401881       4.036727       {txt}Skewness      {res} .0293361
{txt}99%    {res} 2.682605       4.036727       {txt}Kurtosis      {res} 4.966479

{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Predictive margins{col 47}Number of obs{col 65}= {res}  11,764,378

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918{txt}{col 47}Subpop. no. obs{col 65}={res}   11,079,265
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 47}Average RVI{col 65}= {res}      0.0000
{txt}{col 47}Largest FMI{col 65}= {res}      0.0001
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      914.96
{txt}{col 47}        avg{col 65}= {res}      914.99
{txt}Within VCE type: {ralign 12:{res:Delta-method}}{col 47}        max{col 65}= {res}      915.00

{txt}Expression{col 14}: {res}Pr(Suic), predict(pr)

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-4.036727}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-2.422036}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-.8073453}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}.8073453}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}2.422036}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}4.036727}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}_at#Female {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .0002599{col 26}{space 2} .0000113{col 37}{space 1}   23.08{col 46}{space 3}0.000{col 54}{space 4} .0002378{col 67}{space 3}  .000282
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .0000671{col 26}{space 2} 4.61e-06{col 37}{space 1}   14.58{col 46}{space 3}0.000{col 54}{space 4} .0000581{col 67}{space 3} .0000762
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .0002542{col 26}{space 2} 6.61e-06{col 37}{space 1}   38.43{col 46}{space 3}0.000{col 54}{space 4} .0002412{col 67}{space 3} .0002671
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0000647{col 26}{space 2} 2.86e-06{col 37}{space 1}   22.67{col 46}{space 3}0.000{col 54}{space 4} .0000591{col 67}{space 3} .0000703
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2} .0002485{col 26}{space 2} 2.67e-06{col 37}{space 1}   93.15{col 46}{space 3}0.000{col 54}{space 4} .0002433{col 67}{space 3} .0002537
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0000624{col 26}{space 2} 1.33e-06{col 37}{space 1}   47.04{col 46}{space 3}0.000{col 54}{space 4} .0000598{col 67}{space 3}  .000065
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2}  .000243{col 26}{space 2} 3.36e-06{col 37}{space 1}   72.33{col 46}{space 3}0.000{col 54}{space 4} .0002364{col 67}{space 3} .0002496
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0000601{col 26}{space 2} 8.97e-07{col 37}{space 1}   67.06{col 46}{space 3}0.000{col 54}{space 4} .0000584{col 67}{space 3} .0000619
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} .0002376{col 26}{space 2} 7.15e-06{col 37}{space 1}   33.24{col 46}{space 3}0.000{col 54}{space 4} .0002235{col 67}{space 3} .0002516
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2}  .000058{col 26}{space 2} 2.06e-06{col 37}{space 1}   28.21{col 46}{space 3}0.000{col 54}{space 4} .0000539{col 67}{space 3}  .000062
{txt}{space 8}6 0  {c |}{col 14}{res}{space 2} .0002323{col 26}{space 2}  .000011{col 37}{space 1}   21.05{col 46}{space 3}0.000{col 54}{space 4} .0002106{col 67}{space 3} .0002539
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0000559{col 26}{space 2} 3.33e-06{col 37}{space 1}   16.77{col 46}{space 3}0.000{col 54}{space 4} .0000494{col 67}{space 3} .0000624
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_AgeGrp4 AgeGrp4 5 `model'

                    {txt}std_same_prop_AgeGrp4
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.469153      -5.047376
{txt} 5%    {res}-1.445343      -5.047376
{txt}10%    {res}-1.068901      -5.047376       {txt}Obs         {res}135,582,733
{txt}25%    {res} -.504598      -5.047376       {txt}Sum of Wgt. {res}  135582733

{txt}50%    {res} .0808892                      {txt}Mean          {res}  .127631
                        {txt}Largest       Std. Dev.     {res} 1.053953
{txt}75%    {res} .6954771       6.771116
{txt}90%    {res} 1.347035       6.771116       {txt}Variance      {res} 1.110817
{txt}95%    {res} 1.891168       6.771116       {txt}Skewness      {res} .3782019
{txt}99%    {res} 2.953919       6.771116       {txt}Kurtosis      {res}  5.03041

{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Predictive margins{col 47}Number of obs{col 65}= {res}  11,764,378

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918{txt}{col 47}Subpop. no. obs{col 65}={res}   11,079,265
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 47}Average RVI{col 65}= {res}      0.0002
{txt}{col 47}Largest FMI{col 65}= {res}      0.0012
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      913.83
{txt}{col 47}        avg{col 65}= {res}      914.78
{txt}Within VCE type: {ralign 12:{res:Delta-method}}{col 47}        max{col 65}= {res}      914.98

{txt}Expression{col 14}: {res}Pr(Suic), predict(pr)

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-5.047376}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-2.683678}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-.3199793}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}2.043719}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}4.407417}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}6.771116}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}_at#AgeGrp4 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0000947{col 26}{space 2} 8.57e-06{col 37}{space 1}   11.05{col 46}{space 3}0.000{col 54}{space 4} .0000779{col 67}{space 3} .0001115
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0002587{col 26}{space 2} .0000128{col 37}{space 1}   20.25{col 46}{space 3}0.000{col 54}{space 4} .0002337{col 67}{space 3} .0002838
{txt}{space 8}1 3  {c |}{col 14}{res}{space 2} .0002095{col 26}{space 2} 9.56e-06{col 37}{space 1}   21.92{col 46}{space 3}0.000{col 54}{space 4} .0001907{col 67}{space 3} .0002282
{txt}{space 8}1 4  {c |}{col 14}{res}{space 2} .0001308{col 26}{space 2} .0000107{col 37}{space 1}   12.21{col 46}{space 3}0.000{col 54}{space 4} .0001097{col 67}{space 3} .0001518
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0000861{col 26}{space 2} 4.34e-06{col 37}{space 1}   19.81{col 46}{space 3}0.000{col 54}{space 4} .0000775{col 67}{space 3} .0000946
{txt}{space 8}2 2  {c |}{col 14}{res}{space 2} .0002133{col 26}{space 2} 6.18e-06{col 37}{space 1}   34.53{col 46}{space 3}0.000{col 54}{space 4} .0002012{col 67}{space 3} .0002255
{txt}{space 8}2 3  {c |}{col 14}{res}{space 2} .0001989{col 26}{space 2} 5.07e-06{col 37}{space 1}   39.19{col 46}{space 3}0.000{col 54}{space 4} .0001889{col 67}{space 3} .0002088
{txt}{space 8}2 4  {c |}{col 14}{res}{space 2} .0001416{col 26}{space 2} 6.14e-06{col 37}{space 1}   23.07{col 46}{space 3}0.000{col 54}{space 4} .0001295{col 67}{space 3} .0001536
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0000782{col 26}{space 2} 1.64e-06{col 37}{space 1}   47.64{col 46}{space 3}0.000{col 54}{space 4}  .000075{col 67}{space 3} .0000814
{txt}{space 8}3 2  {c |}{col 14}{res}{space 2} .0001759{col 26}{space 2} 2.08e-06{col 37}{space 1}   84.38{col 46}{space 3}0.000{col 54}{space 4} .0001718{col 67}{space 3}   .00018
{txt}{space 8}3 3  {c |}{col 14}{res}{space 2} .0001888{col 26}{space 2} 2.10e-06{col 37}{space 1}   89.98{col 46}{space 3}0.000{col 54}{space 4} .0001847{col 67}{space 3} .0001929
{txt}{space 8}3 4  {c |}{col 14}{res}{space 2} .0001532{col 26}{space 2} 2.30e-06{col 37}{space 1}   66.74{col 46}{space 3}0.000{col 54}{space 4} .0001487{col 67}{space 3} .0001577
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0000711{col 26}{space 2} 3.07e-06{col 37}{space 1}   23.13{col 46}{space 3}0.000{col 54}{space 4}  .000065{col 67}{space 3} .0000771
{txt}{space 8}4 2  {c |}{col 14}{res}{space 2}  .000145{col 26}{space 2} 2.69e-06{col 37}{space 1}   53.92{col 46}{space 3}0.000{col 54}{space 4} .0001398{col 67}{space 3} .0001503
{txt}{space 8}4 3  {c |}{col 14}{res}{space 2} .0001793{col 26}{space 2} 4.00e-06{col 37}{space 1}   44.76{col 46}{space 3}0.000{col 54}{space 4} .0001714{col 67}{space 3} .0001871
{txt}{space 8}4 4  {c |}{col 14}{res}{space 2} .0001659{col 26}{space 2} 6.93e-06{col 37}{space 1}   23.94{col 46}{space 3}0.000{col 54}{space 4} .0001523{col 67}{space 3} .0001795
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} .0000646{col 26}{space 2} 5.34e-06{col 37}{space 1}   12.10{col 46}{space 3}0.000{col 54}{space 4} .0000541{col 67}{space 3} .0000751
{txt}{space 8}5 2  {c |}{col 14}{res}{space 2} .0001196{col 26}{space 2} 4.55e-06{col 37}{space 1}   26.26{col 46}{space 3}0.000{col 54}{space 4} .0001107{col 67}{space 3} .0001285
{txt}{space 8}5 3  {c |}{col 14}{res}{space 2} .0001702{col 26}{space 2} 7.18e-06{col 37}{space 1}   23.72{col 46}{space 3}0.000{col 54}{space 4} .0001561{col 67}{space 3} .0001843
{txt}{space 8}5 4  {c |}{col 14}{res}{space 2} .0001796{col 26}{space 2} .0000144{col 37}{space 1}   12.46{col 46}{space 3}0.000{col 54}{space 4} .0001513{col 67}{space 3} .0002078
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0000587{col 26}{space 2} 7.27e-06{col 37}{space 1}    8.07{col 46}{space 3}0.000{col 54}{space 4} .0000444{col 67}{space 3}  .000073
{txt}{space 8}6 2  {c |}{col 14}{res}{space 2} .0000986{col 26}{space 2} 5.80e-06{col 37}{space 1}   17.01{col 46}{space 3}0.000{col 54}{space 4} .0000872{col 67}{space 3}   .00011
{txt}{space 8}6 3  {c |}{col 14}{res}{space 2} .0001616{col 26}{space 2} .0000102{col 37}{space 1}   15.89{col 46}{space 3}0.000{col 54}{space 4} .0001416{col 67}{space 3} .0001815
{txt}{space 8}6 4  {c |}{col 14}{res}{space 2} .0001944{col 26}{space 2} .0000232{col 37}{space 1}    8.36{col 46}{space 3}0.000{col 54}{space 4} .0001488{col 67}{space 3}   .00024
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_Race5 Race5 5 `model'

                     {txt}std_same_prop_Race5
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.270736      -3.614547
{txt} 5%    {res}-1.387242      -3.614547
{txt}10%    {res}-.9511417      -3.614547       {txt}Obs         {res}135,582,733
{txt}25%    {res}-.2595515      -3.614547       {txt}Sum of Wgt. {res}  135582733

{txt}50%    {res} .4283832                      {txt}Mean          {res} .4242603
                        {txt}Largest       Std. Dev.     {res} 1.233905
{txt}75%    {res} 1.013094       8.750521
{txt}90%    {res} 1.238259       8.750521       {txt}Variance      {res} 1.522523
{txt}95%    {res} 2.074838       8.750521       {txt}Skewness      {res} 1.661957
{txt}99%    {res} 6.478749       8.750521       {txt}Kurtosis      {res} 11.30467

{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Predictive margins{col 47}Number of obs{col 65}= {res}  11,764,378

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918{txt}{col 47}Subpop. no. obs{col 65}={res}   11,079,265
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 47}Average RVI{col 65}= {res}      0.0000
{txt}{col 47}Largest FMI{col 65}= {res}      0.0001
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      914.95
{txt}{col 47}        avg{col 65}= {res}      914.99
{txt}Within VCE type: {ralign 12:{res:Delta-method}}{col 47}        max{col 65}= {res}      915.01

{txt}Expression{col 14}: {res}Pr(Suic), predict(pr)

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 2}-3.614547}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 2}-1.141534}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 4}1.33148}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}3.804493}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}6.277507}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}8.750521}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}_at#Race5 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0001957{col 26}{space 2} .0000101{col 37}{space 1}   19.36{col 46}{space 3}0.000{col 54}{space 4} .0001759{col 67}{space 3} .0002156
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0000836{col 26}{space 2} 9.79e-06{col 37}{space 1}    8.54{col 46}{space 3}0.000{col 54}{space 4} .0000644{col 67}{space 3} .0001028
{txt}{space 8}1 3  {c |}{col 14}{res}{space 2} .0001179{col 26}{space 2} .0000271{col 37}{space 1}    4.35{col 46}{space 3}0.000{col 54}{space 4} .0000647{col 67}{space 3}  .000171
{txt}{space 8}1 4  {c |}{col 14}{res}{space 2} .0000786{col 26}{space 2} 8.42e-06{col 37}{space 1}    9.34{col 46}{space 3}0.000{col 54}{space 4} .0000621{col 67}{space 3} .0000952
{txt}{space 8}1 5  {c |}{col 14}{res}{space 2} .0000589{col 26}{space 2} 6.56e-06{col 37}{space 1}    8.99{col 46}{space 3}0.000{col 54}{space 4}  .000046{col 67}{space 3} .0000718
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2}  .000179{col 26}{space 2} 2.94e-06{col 37}{space 1}   60.91{col 46}{space 3}0.000{col 54}{space 4} .0001732{col 67}{space 3} .0001848
{txt}{space 8}2 2  {c |}{col 14}{res}{space 2} .0000725{col 26}{space 2} 4.02e-06{col 37}{space 1}   18.03{col 46}{space 3}0.000{col 54}{space 4} .0000646{col 67}{space 3} .0000804
{txt}{space 8}2 3  {c |}{col 14}{res}{space 2} .0001431{col 26}{space 2} .0000167{col 37}{space 1}    8.55{col 46}{space 3}0.000{col 54}{space 4} .0001103{col 67}{space 3}  .000176
{txt}{space 8}2 4  {c |}{col 14}{res}{space 2} .0000917{col 26}{space 2} 6.60e-06{col 37}{space 1}   13.89{col 46}{space 3}0.000{col 54}{space 4} .0000787{col 67}{space 3} .0001046
{txt}{space 8}2 5  {c |}{col 14}{res}{space 2} .0000716{col 26}{space 2} 4.50e-06{col 37}{space 1}   15.92{col 46}{space 3}0.000{col 54}{space 4} .0000628{col 67}{space 3} .0000804
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0001637{col 26}{space 2} 3.81e-06{col 37}{space 1}   42.91{col 46}{space 3}0.000{col 54}{space 4} .0001562{col 67}{space 3} .0001712
{txt}{space 8}3 2  {c |}{col 14}{res}{space 2} .0000629{col 26}{space 2} 1.82e-06{col 37}{space 1}   34.63{col 46}{space 3}0.000{col 54}{space 4} .0000593{col 67}{space 3} .0000665
{txt}{space 8}3 3  {c |}{col 14}{res}{space 2} .0001738{col 26}{space 2} .0000129{col 37}{space 1}   13.52{col 46}{space 3}0.000{col 54}{space 4} .0001486{col 67}{space 3}  .000199
{txt}{space 8}3 4  {c |}{col 14}{res}{space 2} .0001068{col 26}{space 2} 4.73e-06{col 37}{space 1}   22.59{col 46}{space 3}0.000{col 54}{space 4} .0000976{col 67}{space 3} .0001161
{txt}{space 8}3 5  {c |}{col 14}{res}{space 2}  .000087{col 26}{space 2} 3.04e-06{col 37}{space 1}   28.60{col 46}{space 3}0.000{col 54}{space 4} .0000811{col 67}{space 3}  .000093
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0001497{col 26}{space 2} 8.84e-06{col 37}{space 1}   16.93{col 46}{space 3}0.000{col 54}{space 4} .0001323{col 67}{space 3}  .000167
{txt}{space 8}4 2  {c |}{col 14}{res}{space 2} .0000545{col 26}{space 2} 4.56e-06{col 37}{space 1}   11.97{col 46}{space 3}0.000{col 54}{space 4} .0000456{col 67}{space 3} .0000635
{txt}{space 8}4 3  {c |}{col 14}{res}{space 2} .0002111{col 26}{space 2} .0000354{col 37}{space 1}    5.96{col 46}{space 3}0.000{col 54}{space 4} .0001415{col 67}{space 3} .0002806
{txt}{space 8}4 4  {c |}{col 14}{res}{space 2} .0001245{col 26}{space 2} 5.27e-06{col 37}{space 1}   23.62{col 46}{space 3}0.000{col 54}{space 4} .0001142{col 67}{space 3} .0001349
{txt}{space 8}4 5  {c |}{col 14}{res}{space 2} .0001058{col 26}{space 2} 6.87e-06{col 37}{space 1}   15.39{col 46}{space 3}0.000{col 54}{space 4} .0000923{col 67}{space 3} .0001193
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} .0001369{col 26}{space 2} .0000131{col 37}{space 1}   10.48{col 46}{space 3}0.000{col 54}{space 4} .0001112{col 67}{space 3} .0001625
{txt}{space 8}5 2  {c |}{col 14}{res}{space 2} .0000473{col 26}{space 2} 6.94e-06{col 37}{space 1}    6.82{col 46}{space 3}0.000{col 54}{space 4} .0000337{col 67}{space 3} .0000609
{txt}{space 8}5 3  {c |}{col 14}{res}{space 2} .0002563{col 26}{space 2} .0000733{col 37}{space 1}    3.50{col 46}{space 3}0.000{col 54}{space 4} .0001124{col 67}{space 3} .0004002
{txt}{space 8}5 4  {c |}{col 14}{res}{space 2} .0001452{col 26}{space 2} 9.94e-06{col 37}{space 1}   14.61{col 46}{space 3}0.000{col 54}{space 4} .0001257{col 67}{space 3} .0001647
{txt}{space 8}5 5  {c |}{col 14}{res}{space 2} .0001286{col 26}{space 2} .0000146{col 37}{space 1}    8.79{col 46}{space 3}0.000{col 54}{space 4} .0000999{col 67}{space 3} .0001573
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0001252{col 26}{space 2} .0000165{col 37}{space 1}    7.58{col 46}{space 3}0.000{col 54}{space 4} .0000927{col 67}{space 3} .0001576
{txt}{space 8}6 2  {c |}{col 14}{res}{space 2}  .000041{col 26}{space 2} 8.65e-06{col 37}{space 1}    4.74{col 46}{space 3}0.000{col 54}{space 4} .0000241{col 67}{space 3}  .000058
{txt}{space 8}6 3  {c |}{col 14}{res}{space 2} .0003112{col 26}{space 2} .0001269{col 37}{space 1}    2.45{col 46}{space 3}0.014{col 54}{space 4} .0000621{col 67}{space 3} .0005604
{txt}{space 8}6 4  {c |}{col 14}{res}{space 2} .0001692{col 26}{space 2} .0000174{col 37}{space 1}    9.70{col 46}{space 3}0.000{col 54}{space 4}  .000135{col 67}{space 3} .0002035
{txt}{space 8}6 5  {c |}{col 14}{res}{space 2} .0001563{col 26}{space 2} .0000258{col 37}{space 1}    6.05{col 46}{space 3}0.000{col 54}{space 4} .0001055{col 67}{space 3}  .000207
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_BornUSA BornUSA 5 `model'

                    {txt}std_same_prop_BornUSA
{hline 61}
      Percentiles      Smallest
 1%    {res}-5.045306      -7.936538
{txt} 5%    {res}-2.723737      -7.936538
{txt}10%    {res}-1.754185      -7.936538       {txt}Obs         {res}135,582,733
{txt}25%    {res}-.5298624      -7.936538       {txt}Sum of Wgt. {res}  135582733

{txt}50%    {res} .1534955                      {txt}Mean          {res}-.1095675
                        {txt}Largest       Std. Dev.     {res} 1.400314
{txt}75%    {res} .6318931       7.936538
{txt}90%    {res} .8333296       7.936538       {txt}Variance      {res} 1.960879
{txt}95%    {res} .9703126       7.936538       {txt}Skewness      {res}-.7379761
{txt}99%    {res} 4.547946       7.936538       {txt}Kurtosis      {res} 8.840372

{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Predictive margins{col 47}Number of obs{col 65}= {res}  11,764,378

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918{txt}{col 47}Subpop. no. obs{col 65}={res}   11,079,265
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 47}Average RVI{col 65}= {res}      0.0000
{txt}{col 47}Largest FMI{col 65}= {res}      0.0000
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      914.99
{txt}{col 47}        avg{col 65}= {res}      915.00
{txt}Within VCE type: {ralign 12:{res:Delta-method}}{col 47}        max{col 65}= {res}      915.00

{txt}Expression{col 14}: {res}Pr(Suic), predict(pr)

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 2}-7.936538}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 2}-4.761923}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 2}-1.587308}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}1.587308}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}4.761923}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}7.936538}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}_at#BornUSA {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .0001419{col 26}{space 2}  .000024{col 37}{space 1}    5.92{col 46}{space 3}0.000{col 54}{space 4} .0000949{col 67}{space 3} .0001889
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .0001094{col 26}{space 2} 7.21e-06{col 37}{space 1}   15.16{col 46}{space 3}0.000{col 54}{space 4} .0000952{col 67}{space 3} .0001235
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .0001238{col 26}{space 2} .0000141{col 37}{space 1}    8.75{col 46}{space 3}0.000{col 54}{space 4}  .000096{col 67}{space 3} .0001516
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0001272{col 26}{space 2} 4.76e-06{col 37}{space 1}   26.74{col 46}{space 3}0.000{col 54}{space 4} .0001179{col 67}{space 3} .0001365
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2}  .000108{col 26}{space 2} 6.68e-06{col 37}{space 1}   16.17{col 46}{space 3}0.000{col 54}{space 4} .0000949{col 67}{space 3} .0001211
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0001479{col 26}{space 2} 1.63e-06{col 37}{space 1}   90.82{col 46}{space 3}0.000{col 54}{space 4} .0001447{col 67}{space 3} .0001511
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2} .0000942{col 26}{space 2} 2.72e-06{col 37}{space 1}   34.68{col 46}{space 3}0.000{col 54}{space 4} .0000889{col 67}{space 3} .0000996
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2}  .000172{col 26}{space 2} 3.91e-06{col 37}{space 1}   43.97{col 46}{space 3}0.000{col 54}{space 4} .0001643{col 67}{space 3} .0001797
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} .0000822{col 26}{space 2} 5.25e-06{col 37}{space 1}   15.65{col 46}{space 3}0.000{col 54}{space 4} .0000719{col 67}{space 3} .0000925
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2}    .0002{col 26}{space 2} .0000102{col 37}{space 1}   19.67{col 46}{space 3}0.000{col 54}{space 4}   .00018{col 67}{space 3}   .00022
{txt}{space 8}6 0  {c |}{col 14}{res}{space 2} .0000717{col 26}{space 2} 8.36e-06{col 37}{space 1}    8.58{col 46}{space 3}0.000{col 54}{space 4} .0000553{col 67}{space 3} .0000881
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0002326{col 26}{space 2} .0000185{col 37}{space 1}   12.57{col 46}{space 3}0.000{col 54}{space 4} .0001963{col 67}{space 3} .0002689
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_MarStat5 MarStat5 5 `model'

                   {txt}std_same_prop_MarStat5
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.292691      -4.824302
{txt} 5%    {res}-1.574807      -4.824302
{txt}10%    {res}-1.168543      -4.824302       {txt}Obs         {res}135,582,272
{txt}25%    {res}-.5012236      -4.824302       {txt}Sum of Wgt. {res}  135582272

{txt}50%    {res} .1833285                      {txt}Mean          {res} .1423099
                        {txt}Largest       Std. Dev.     {res} 1.051846
{txt}75%    {res} .8066256         5.1647
{txt}90%    {res} 1.365528         5.1647       {txt}Variance      {res}  1.10638
{txt}95%    {res} 1.765109         5.1647       {txt}Skewness      {res} .0184338
{txt}99%    {res} 2.683285         5.1647       {txt}Kurtosis      {res}  4.57374

{txt}Multiple-imputation estimates{col 47}Imputations{col 65}= {res}          10
{txt}Predictive margins{col 47}Number of obs{col 65}= {res}  11,764,378

{txt}{col 1}Number of strata{col 19}= {res}        1{txt}{col 47}Population size{col 65}={res}  418,786,443
{txt}{col 1}Number of PSUs{col 19}= {res}      918{txt}{col 47}Subpop. no. obs{col 65}={res}   11,079,265
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 47}Average RVI{col 65}= {res}      0.0020
{txt}{col 47}Largest FMI{col 65}= {res}      0.0069
{txt}{col 47}Complete DF{col 65}= {res}         917
{txt}DF adjustment:{ralign 15: {res:Small sample}}{col 47}DF:     min{col 65}= {res}      904.42
{txt}{col 47}        avg{col 65}= {res}      911.56
{txt}Within VCE type: {ralign 12:{res:Delta-method}}{col 47}        max{col 65}= {res}      914.19

{txt}Expression{col 14}: {res}Pr(Suic), predict(pr)

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-4.824302}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-2.826501}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-.8287008}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 5}1.1691}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 5}3.1669}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 5}5.1647}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#MarStat5 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0001231{col 26}{space 2} 6.85e-06{col 37}{space 1}   17.96{col 46}{space 3}0.000{col 54}{space 4} .0001096{col 67}{space 3} .0001365
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0003518{col 26}{space 2} .0000352{col 37}{space 1}   10.00{col 46}{space 3}0.000{col 54}{space 4} .0002827{col 67}{space 3} .0004208
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{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}. 
.         if (`model_version' == 6) {c -(}
.                 estimates restore m1
.                 margin_interact std_same_prop_UnEmpl UnEmpl 5 `model'
.                 estimates restore m1
.                 margin_interact std_same_prop_PhysProb PhysProb 5 `model'
.         {c )-}
. 
. {c )-}
{txt}
{com}. 
. 
. log close 
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/N/project/suicide_study/pnas_replication/results/log/mi_5.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}20 Aug 2020, 20:34:33
{txt}{.-}
{smcl}
{txt}{sf}{ul off}